Martin Mladenov

59 papers A* 17A 7B 1C 1Journal 25Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	All that Glitters is not Gold: Uncovering Exposed Industrial Control Systems and Honeypots in the Wild. EuroS&P Martin Mladenov, László Erdodi, Georgios Smaragdakis
2024	A*	`conf`	Demystifying Embedding Spaces using Large Language Models. ICLR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2024	A*	`conf`	Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies. SIGIR Chih-Wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz, Craig Boutilier
2024	J	`jnl`	Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies. CoRR Chih-Wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz, Craig Boutilier
2024	A*	`conf`	Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization. AAAI Craig Boutilier, Martin Mladenov, Guy Tennenholtz
2024	J	`jnl`	Report on the 1st Workshop on Simulations for Information Access (Sim4IA 2024) at SIGIR 2024. SIGIR Forum Timo Breuer, Christin Katharina Kreutz, Norbert Fuhr, Krisztian Balog, Philipp Schaer, Nolwenn Bernard, Ingo Frommholz, Marcel Gohsen, Kaixin Ji, Gareth J. F. Jones, Jüri Keller, Jiqun Liu, Martin Mladenov, Gabriella Pasi, Johanne R. Trippas, Xi Wang, Saber Zerhoudi, ChengXiang Zhai
2024	J	`jnl`	Report on the Workshop on Simulations for Information Access (Sim4IA 2024) at SIGIR 2024. CoRR Timo Breuer, Christin Katharina Kreutz, Norbert Fuhr, Krisztian Balog, Philipp Schaer, Nolwenn Bernard, Ingo Frommholz, Marcel Gohsen, Kaixin Ji, Gareth J. F. Jones, Jüri Keller, Jiqun Liu, Martin Mladenov, Gabriella Pasi, Johanne R. Trippas, Xi Wang, Saber Zerhoudi, ChengXiang Zhai
2023	J	`jnl`	Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems. CoRR Siddharth Prasad, Martin Mladenov, Craig Boutilier
2023	J	`jnl`	Demystifying Embedding Spaces using Large Language Models. CoRR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2023	—	`conf`	Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. WWW (Companion Volume) Abhishek Naik, Bo Chang, Alexandros Karatzoglou, Martin Mladenov, Ed H. Chi, Minmin Chen
2023	J	`jnl`	Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models. CoRR Craig Boutilier, Martin Mladenov, Guy Tennenholtz
2023	J	`jnl`	Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics. CoRR Guy Tennenholtz, Martin Mladenov, Nadav Merlis, Craig Boutilier
2023	A*	`conf`	Reinforcement Learning with History Dependent Dynamic Contexts. ICML Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier
2023	J	`jnl`	Reinforcement Learning with History-Dependent Dynamic Contexts. CoRR Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier
2022	—	`conf`	An adversarial variational inference approach for travel demand calibration of urban traffic simulators. SIGSPATIAL/GIS Martin Mladenov, Sanjay Ganapathy Subramaniam, Chih-Wei Hsu, Neha Arora, Andrew Tomkins, Craig Boutilier, Carolina Osorio
2021	A*	`conf`	Meta-Thompson Sampling. ICML Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári
2021	J	`jnl`	Meta-Thompson Sampling. CoRR Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári
2021	J	`jnl`	RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems. CoRR Martin Mladenov, Chih-Wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier
2021	A*	`conf`	Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. WWW Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
2021	J	`jnl`	Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. CoRR Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
2020	A	`conf`	Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG. RecSys Martin Mladenov, Chih-Wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier
2020	J	`jnl`	Differentiable Bandit Exploration. CoRR Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
2020	J	`jnl`	Differentiable Meta-Learning in Contextual Bandits. CoRR Branislav Kveton, Martin Mladenov, Chih-Wei Hsu, Manzil Zaheer, Csaba Szepesvári, Craig Boutilier
2020	A*	`conf`	Differentiable Meta-Learning of Bandit Policies. NeurIPS Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
2020	A*	`conf`	Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. ICML Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier
2020	J	`jnl`	Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. CoRR Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier
2019	A*	`conf`	Advantage Amplification in Slowly Evolving Latent-State Environments. IJCAI Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier
2019	J	`jnl`	Advantage Amplification in Slowly Evolving Latent-State Environments. CoRR Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier
2019	J	`jnl`	Empirical Bayes Regret Minimization. CoRR Chih-Wei Hsu, Branislav Kveton, Ofer Meshi, Martin Mladenov, Csaba Szepesvári
2019	J	`jnl`	RecSim: A Configurable Simulation Platform for Recommender Systems. CoRR Eugene Ie, Chih-Wei Hsu, Martin Mladenov, Vihan Jain, Sanmit Narvekar, Jing Wang, Rui Wu, Craig Boutilier
2018	A*	`conf`	Efficient Symbolic Integration for Probabilistic Inference. IJCAI Samuel Kolb, Martin Mladenov, Scott Sanner, Vaishak Belle, Kristian Kersting
2018	A*	`conf`	Planning and Learning with Stochastic Action Sets. IJCAI Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans
2018	J	`jnl`	Planning and Learning with Stochastic Action Sets. CoRR Craig Boutilier, Alon Cohen, Amit Daniely, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans
2017	A*	`conf`	Lifted Inference for Convex Quadratic Programs. AAAI Martin Mladenov, Leonard Kleinhans, Kristian Kersting
2017	A*	`conf`	Logistic Markov Decision Processes. IJCAI Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu
2017	J	`jnl`	Relational linear programming. Artif. Intell. Kristian Kersting, Martin Mladenov, Pavel Tokmakov
2017	A*	`conf`	The Symbolic Interior Point Method. AAAI Martin Mladenov, Vaishak Belle, Kristian Kersting
2016	J	`jnl`	Lifted Convex Quadratic Programming. CoRR Martin Mladenov, Leonard Kleinhans, Kristian Kersting
2016	—	`conf`	RELOOP: A Python-Embedded Declarative Language for Relational Optimization. AAAI Workshop: Declarative Learning Based Programming Martin Mladenov, Danny Heinrich, Leonard Kleinhans, Felix Gonsior, Kristian Kersting
2016	J	`jnl`	The Symbolic Interior Point Method. CoRR Martin Mladenov, Vaishak Belle, Kristian Kersting
2015	A*	`conf`	Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation. IJCAI Fabian Hadiji, Martin Mladenov, Christian Bauckhage, Kristian Kersting
2015	A	`conf`	Equitable Partitions of Concave Free Energies. UAI Martin Mladenov, Kristian Kersting
2014	A	`conf`	Dimension Reduction via Colour Refinement. ESA Martin Grohe, Kristian Kersting, Martin Mladenov, Erkal Selman
2014	A	`conf`	Efficient Lifting of MAP LP Relaxations Using k-Locality. AISTATS Martin Mladenov, Kristian Kersting, Amir Globerson
2014	A	`conf`	Lifted Message Passing as Reparametrization of Graphical Models. UAI Martin Mladenov, Amir Globerson, Kristian Kersting
2014	A*	`conf`	Lifting Relational MAP-LPs Using Cluster Signatures. AAAI Udi Apsel, Kristian Kersting, Martin Mladenov
2014	—	`conf`	Lifting Relational MAP-LPs using Cluster Signatures. StarAI@AAAI Udi Apsel, Kristian Kersting, Martin Mladenov
2014	A*	`conf`	Power Iterated Color Refinement. AAAI Kristian Kersting, Martin Mladenov, Roman Garnett, Martin Grohe
2014	J	`jnl`	Relational Linear Programs. CoRR Kristian Kersting, Martin Mladenov, Pavel Tokmakov
2013	J	`jnl`	Dimension Reduction via Colour Refinement. CoRR Martin Grohe, Kristian Kersting, Martin Mladenov, Erkal Selman
2013	J	`jnl`	Exploiting symmetries for scaling loopy belief propagation and relational training. Mach. Learn. Babak Ahmadi, Kristian Kersting, Martin Mladenov, Sriraam Natarajan
2013	—	`conf`	Lifted Inference via k-Locality. StarAI@AAAI Martin Mladenov, Kristian Kersting
2012	J	`jnl`	Identifying Place Histories from Activity Traces with an Eye to Parameter Impact. IEEE Trans. Vis. Comput. Graph. Gennady L. Andrienko, Natalia V. Andrienko, Martin Mladenov, Michael Mock, Christian Pölitz
2012	A	`conf`	Lifted Linear Programming. AISTATS Martin Mladenov, Babak Ahmadi, Kristian Kersting
2012	B	`conf`	Pairwise Markov Logic. ILP Daan Fierens, Kristian Kersting, Jesse Davis, Jian Chen, Martin Mladenov
2011	—	`conf`	On Lifted PageRank, Kalman Filter and Towards Lifted Linear Program Solving. LWA Babak Ahmadi, Martin Mladenov, Kristian Kersting, Scott Sanner
2010	—	`conf`	Discovering bits of place histories from people's activity traces. IEEE VAST Gennady L. Andrienko, Natalia V. Andrienko, Martin Mladenov, Michael Mock, Christian Pölitz
2010	C	`conf`	Extracting Events from Spatial Time Series. IV Gennady L. Andrienko, Natalia V. Andrienko, Martin Mladenov, Michael Mock, Christian Pölitz
2008	—	`conf`	Fault monitoring and correction in a walking robot using LMS filters. WISES Martin Mladenov, Michael Mock, Karl-Erwin Grosspietsch